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http://dx.doi.org/10.9708/jksci.2021.26.09.057

Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft  

Hur, Hwa-La (Dept. of Aeronautical Software Engineering, Kyungwoon University)
Kim, Tae-Sun (Dept. of Avionics Engineering, Kyungwoon University)
Park, Myeong-Chul (Dept. of Avionics Engineering, Kyungwoon University)
Publication Information
Journal of the Korea Society of Computer and Information / v.26, no.9, 2021 , pp. 57-64 More about this Journal
Abstract
In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.
Keywords
Speech Recognition; CNN; MFCC; Flight Controller; TensorFlow;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Myeong-Chul Park et al., "Drone controller using motion imagery brainwave and voice recognition," Proceedings of the Korean Society of Computer Information Conference 28(2), pp. 257-258, July 2020.
2 M. A. Anusuya and S. K. Katti, "Speech Recognition by Machine, A Review," International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 3, pp. 181-205, December 2009.
3 T. N. Sainath, A. Mohamed, B. Kingsbury and B. Ramabhadran, "Deep convolutional neural networks for LVCSR," 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 8614-8618, May 2013. DOI: 10.1109/ICASSP.2013.6639347   DOI
4 Mitra. Vikramjit et al., "Evaluating robust features on Deep Neural Networks for speech recognition in noisy and channel mismatched conditions," Proceedings of the Annual Conference of the International Speech Communication Association, pp. 895-899, September 2014.
5 V. Pratap et al., "Wav2Letter++: A Fast Open-source Speech Recognition System," IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 6460-6464, 2019. DOI: 10.1109/ICASSP.2019.8683535   DOI
6 S. Davis and P. Mermelstein, "Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 28, No. 4, pp. 357-366, August 1980. DOI: 10.1109/TASSP.1980.1163420   DOI
7 Warden. Pete, "Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition," ArXiv Preprint ArXiv:1804.03209, 2018.
8 Soonwon So et al., "Development of Age Classification Deep Learning Algorithm Using Korean Speech," Journal of Biomedical Engineering Research, Vol. 39, pp. 63-68, Apr. 2018. DOI : 10.9718/JBER.2018.39.2.63   DOI
9 A. B. Nassif, I. Shahin, I. Attili, M. Azzeh and K. Shaalan, "Speech Recognition Using Deep Neural Networks: A Systematic Review," IEEE Access, Vol. 7, pp. 19143-19165, 2019. DOI: 10.1109/ACCESS.2019.2896880   DOI
10 Dongyeol Jang, Seungryeol Yoo, "Integrated System of Mobile Manipulator with Speech Recognition and Deep Learning-based Object Detection," The Journal of Korea Robotics Society, Vol. 16(3), pp. 270-275, Sep. 2021. DOI : 10.7746/jkros.2021.16.3.270   DOI
11 Tomasz Rogalskia and Robert Wielgatb, "A concept of voice guided general aviation aircraft," Aerospace Science and Technology, Vol. 14, pp. 321-328, Feb. 2010. DOI : 10.1016/j.ast.2010.02.006   DOI
12 Seongwoo Kim, Mingi Seo, Yunghwan Oh and Bonggyu Kim, "A Study on Cockpit Voice Command System for Fighter Aircraft," KSAS, Vol. 41(12), pp. 1011-1017, Dec. 2013. DOI : 10.5139/JKSAS.2013.41.12.1011   DOI
13 Aziz Siyaev, Geun-Sik Jo, "Towards Aircraft Maintenance Metaverse Using Speech Interactions with Virtual Objects in Mixed Reality," Sensors, 21(6), Mar. 2021. DOI : 10.3390/s21062066   DOI
14 Yu-Yi Lin et al., "A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology," Applied Sciences, Vol. 11(6), Mar. 2021. DOI : 10.3390/app11062477   DOI
15 Ruben Contreras, Angel Ayala and Francisco Cruz, "Unmanned Aerial Vehicle Control through Domain-Based Automatic Speech Recognition," Computers, Vol. 9(3), Sep. 2020. DOI : 10.3390/computers9030075   DOI